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  1. Article ; Online: Detecting and segmenting cell nuclei in two-dimensional microscopy images

    Chi Liu / Fei Shang / John A Ozolek / Gustavo K Rohde

    Journal of Pathology Informatics, Vol 7, Iss 1, Pp 42-

    2016  Volume 42

    Abstract: Introduction: Cell nuclei are important indicators of cellular processes and diseases. Segmentation is an essential stage in systems for quantitative analysis of nuclei extracted from microscopy images. Given the wide variety of nuclei appearance in ... ...

    Abstract Introduction: Cell nuclei are important indicators of cellular processes and diseases. Segmentation is an essential stage in systems for quantitative analysis of nuclei extracted from microscopy images. Given the wide variety of nuclei appearance in different organs and staining procedures, a plethora of methods have been described in the literature to improve the segmentation accuracy and robustness. Materials and Methods: In this paper, we propose an unsupervised method for cell nuclei detection and segmentation in two-dimensional microscopy images. The nuclei in the image are detected automatically using a matching-based method. Next, edge maps are generated at multiple image blurring levels followed by edge selection performed in polar space. The nuclei contours are refined iteratively in the constructed edge pyramid. The validation study was conducted over two cell nuclei datasets with manual labeling, including 25 hematoxylin and eosin-stained liver histopathology images and 35 Papanicolaou-stained thyroid images. Results: The nuclei detection accuracy was measured by miss rate, and the segmentation accuracy was evaluated by two types of error metrics. Overall, the nuclei detection efficiency of the proposed method is similar to the supervised template matching method. In comparison to four existing state-of-the-art segmentation methods, the proposed method performed the best with average segmentation error 10.34% and 0.33 measured by area error rate and normalized sum of distances (×10). Conclusion: Quantitative analysis showed that the method is automatic and accurate when segmenting cell nuclei from microscopy images with noisy background and has the potential to be used in clinic settings.
    Keywords Cell nuclei detection and segmentation ; multiscale method ; pathology images ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Pathology ; RB1-214
    Subject code 571
    Language English
    Publishing date 2016-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Deletion of AMPK minimizes graft-versus-host disease through an early impact on effector donor T cells

    Darlene A. Monlish / Kevin J. Beezhold / Pailin Chiaranunt / Katelyn Paz / Nathan J. Moore / Andrea K. Dobbs / Rebecca A. Brown / John A. Ozolek / Bruce R. Blazar / Craig A. Byersdorfer

    JCI Insight, Vol 6, Iss

    2021  Volume 14

    Abstract: Allogeneic hematopoietic stem cell transplantation is a viable treatment for multiple hematologic diseases, but its application is often limited by graft-versus-host disease (GVHD), where donor T cells attack host tissues in the skin, liver, and ... ...

    Abstract Allogeneic hematopoietic stem cell transplantation is a viable treatment for multiple hematologic diseases, but its application is often limited by graft-versus-host disease (GVHD), where donor T cells attack host tissues in the skin, liver, and gastrointestinal tract. Here, we examined the role of the cellular energy sensor AMP kinase (AMPK) in alloreactive T cells during GVHD development. Early posttransplant, AMPK activity increased more than 15-fold in allogeneic T cells, and transplantation of T cells deficient in both AMPKα1 and AMPKα2 decreased GVHD severity in multiple disease models. Importantly, a lack of AMPK lessened GVHD without compromising antileukemia responses or impairing lymphopenia-driven immune reconstitution. Mechanistically, absence of AMPK decreased both CD4+ and CD8+ effector T cell numbers as early as day 3 posttransplant, while simultaneously increasing regulatory T cell (Treg) percentages. Improvements in GVHD resulted from cell-intrinsic perturbations in conventional effector T cells as depletion of donor Tregs had minimal impact on AMPK-related improvements. Together, these results highlight a specific role for AMPK in allogeneic effector T cells early posttransplant and suggest that AMPK inhibition may be an innovative approach to mitigate GVHD while preserving graft-versus-leukemia responses and maintaining robust immune reconstitution.
    Keywords Metabolism ; Transplantation ; Medicine ; R
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher American Society for Clinical investigation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Carnegie Mellon University bioimaging day 2014

    Gustavo K Rohde / John A Ozolek / Anil V Parwani / Liron Pantanowitz

    Journal of Pathology Informatics, Vol 5, Iss 1, Pp 32-

    Challenges and opportunities in digital pathology

    2014  Volume 32

    Abstract: Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into ... ...

    Abstract Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into large image files that can be shared, stored, and analyzed rapidly. Many applications around this novel technology have evolved in the last decade including education, research and clinical applications. This publication highlights a collection of abstracts, each corresponding to a talk given at Carnegie Mellon University′s (CMU) Bioimaging Day 2014 co-sponsored by the Biomedical Engineering and Lane Center for Computational Biology Departments at CMU. Topics related specifically to digital pathology are presented in this collection of abstracts. These include topics related to digital workflow implementation, imaging and artifacts, storage demands, and automated image analysis algorithms.
    Keywords Challenges ; digital pathology ; image analysis ; opportunities ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Pathology ; RB1-214
    Subject code 028
    Language English
    Publishing date 2014-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: A General System for Automatic Biomedical Image Segmentation Using Intensity Neighborhoods

    Cheng Chen / John A. Ozolek / Wei Wang / Gustavo K. Rohde

    International Journal of Biomedical Imaging, Vol

    2011  Volume 2011

    Abstract: Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require ... ...

    Abstract Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.
    Keywords Medicine (General) ; R5-920 ; Medical physics. Medical radiology. Nuclear medicine ; R895-920 ; Medical technology ; R855-855.5
    Subject code 004 ; 006
    Language English
    Publishing date 2011-01-01T00:00:00Z
    Publisher Hindawi Publishing Corporation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: A vocabulary for the identification and delineation of teratoma tissue components in hematoxylin and eosin-stained samples

    Ramamurthy Bhagavatula / Michael T McCann / Matthew Fickus / Carlos A Castro / John A Ozolek / Jelena Kovacevic

    Journal of Pathology Informatics, Vol 5, Iss 1, Pp 19-

    2014  Volume 19

    Abstract: We propose a methodology for the design of features mimicking the visual cues used by pathologists when identifying tissues in hematoxylin and eosin (H&E)-stained samples. Background: H&E staining is the gold standard in clinical histology; it is cheap ... ...

    Abstract We propose a methodology for the design of features mimicking the visual cues used by pathologists when identifying tissues in hematoxylin and eosin (H&E)-stained samples. Background: H&E staining is the gold standard in clinical histology; it is cheap and universally used, producing a vast number of histopathological samples. While pathologists accurately and consistently identify tissues and their pathologies, it is a time-consuming and expensive task, establishing the need for automated algorithms for improved throughput and robustness. Methods: We use an iterative feedback process to design a histopathology vocabulary (HV), a concise set of features that mimic the visual cues used by pathologists, e.g. "cytoplasm color" or "nucleus density." These features are based in histology and understood by both pathologists and engineers. We compare our HV to several generic texture-feature sets in a pixel-level classification algorithm. Results: Results on delineating and identifying tissues in teratoma tumor samples validate our expert knowledge-based approach. Conclusions: The HV can be an effective tool for identifying and delineating teratoma components from images of H&E-stained tissue samples.
    Keywords Automated histology ; classification ; segmentation ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Pathology ; RB1-214
    Subject code 004
    Language English
    Publishing date 2014-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: A computer-based automated algorithm for assessing acinar cell loss after experimental pancreatitis.

    John F Eisses / Amy W Davis / Akif Burak Tosun / Zachary R Dionise / Cheng Chen / John A Ozolek / Gustavo K Rohde / Sohail Z Husain

    PLoS ONE, Vol 9, Iss 10, p e

    2014  Volume 110220

    Abstract: The change in exocrine mass is an important parameter to follow in experimental models of pancreatic injury and regeneration. However, at present, the quantitative assessment of exocrine content by histology is tedious and operator-dependent, requiring ... ...

    Abstract The change in exocrine mass is an important parameter to follow in experimental models of pancreatic injury and regeneration. However, at present, the quantitative assessment of exocrine content by histology is tedious and operator-dependent, requiring manual assessment of acinar area on serial pancreatic sections. In this study, we utilized a novel computer-generated learning algorithm to construct an accurate and rapid method of quantifying acinar content. The algorithm works by learning differences in pixel characteristics from input examples provided by human experts. HE-stained pancreatic sections were obtained in mice recovering from a 2-day, hourly caerulein hyperstimulation model of experimental pancreatitis. For training data, a pathologist carefully outlined discrete regions of acinar and non-acinar tissue in 21 sections at various stages of pancreatic injury and recovery (termed the "ground truth"). After the expert defined the ground truth, the computer was able to develop a prediction rule that was then applied to a unique set of high-resolution images in order to validate the process. For baseline, non-injured pancreatic sections, the software demonstrated close agreement with the ground truth in identifying baseline acinar tissue area with only a difference of 1% ± 0.05% (p = 0.21). Within regions of injured tissue, the software reported a difference of 2.5% ± 0.04% in acinar area compared with the pathologist (p = 0.47). Surprisingly, on detailed morphological examination, the discrepancy was primarily because the software outlined acini and excluded inter-acinar and luminal white space with greater precision. The findings suggest that the software will be of great potential benefit to both clinicians and researchers in quantifying pancreatic acinar cell flux in the injured and recovering pancreas.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2014-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Chronic Granulomatous Disease Presenting as Aseptic Ascites in a 2-Year-Old Child

    J. F. Moreau / John A. Ozolek / P. Ling Lin / Todd D. Green / Elaine A. Cassidy / Veena L. Venkat / Andrew R. Buchert

    Case Reports in Immunology, Vol

    2013  Volume 2013

    Keywords Immunologic diseases. Allergy ; RC581-607 ; Specialties of internal medicine ; RC581-951 ; Internal medicine ; RC31-1245 ; Medicine ; R ; DOAJ:Allergy and Immunology ; DOAJ:Medicine (General) ; DOAJ:Health Sciences
    Language English
    Publishing date 2013-01-01T00:00:00Z
    Publisher Hindawi Publishing Corporation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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